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DOE OSTI2025

Remeasurement of the 239 Pu(n,f)/ 235 U(n,f) Cross-Section Ratio with the NIFFTE fission Time Projection Chamber Using Vapor-deposited Targets

The NIFFTE fission Time Projection Chamber (fissionTPC) has been used to measure the 239 Pu(n,f)/ 235 U(n,f) cross-section ratio for neutron-induced fission in the range of 0.1–100 MeV, with high precision. A white neutron source was provided by the Los Alamos Neutron Science Center, where the experiment was conducted as a remeasurement to evaluate a roughly 2% discrepancy of the previous fissionTPC results with ENDF/B-VIII.0. Further, a detailed accounting of measurement uncertainties was performed, based on the fissionTPC's novel ability to provide three-dimensional reconstruction of fission-fragment ionization profiles. Current results obtained using a vapor-deposited, highly uniform 239 Pu target, in comparison to the measurement published in 2021, where a 239 Pu electroplated target was used, are presented and discussed. The remeasurement presented here is in agreement with the previous fissionTPC result within measurement uncertainties.

235U↗

DOE OSTI2025

Cations Enhance Hydride Transfer to Noncatalytic Metals in Concentrated Alkaline Electrolytes

Alkali metal cations are known to influence the kinetics of the hydrogen evolution reaction (HER), acting as either promoters or inhibitors to the rate-determining step depending on the metal surface, local pH, and cation concentration. Despite the importance of concentrated electrolytes for commercial electrochemical cells, the impact of cations on the HER in concentrated alkaline environments (>1 M) and in mixed cation systems remains poorly understood. Here, this study quantifies the HER kinetics at polycrystalline metal surfaces (Pt, Au, Cu, and Fe) and the equilibrium solvation environment in pure and mixed alkali metal hydroxide electrolytes at concentrations up to 3.0 M. Kinetic analyses of Au, Cu, and Fe revealed a positive cation-concentration-effect that was primarily driven by changes to the charge transfer coefficient. Multinuclear NMR spectroscopy examined the solvation of H 2 O/OH – species and the alkali cations as a function of (mixed) alkali cation concentration(s), and demonstrated rapid exchange between solvent, hydroxide, and solvated cations. Together, these findings support models where HER kinetics on noncatalytic metal surfaces in strongly alkaline conditions are primarily governed by the average polarization and polarizability of the metal/solution interface and that increasing cation activity continues to increase the transfer coefficient at metal-hydroxide concentrations up to 3.0 M. Electrolytes and additives which can outcompete weakly hydrated cations and disrupt the interfacial water structure are expected to suppress parasitic HER at electrodes for energy storage and electroplating.

Cations↗

DOE OSTI2026

Toward Lithium Recovery Using Modular (and Membraneless) Phase Separation and Extraction (MPSE) Technology with Ionic Liquid (IL) Solvents: Effect of Coatings

In this work, a single-channel slope-plate Modular and Membrane-less Phase Separation and Extraction (MPSE) device was fabricated using 3D printing. The slope-plate was designed with an insertable glass slide to enable surface modification with coatings. Self-assembled monolayers (SAMs) and perfluoropolyether (Zdol) coatings were applied to tailor surface wettability and enhance phase separation. Using a model biphasic system of water and hexadecane, both coatings significantly improved the separation efficiency compared to the uncoated device by promoting selective wetting. Building on these results, lithium extraction from a simulated saline solution was investigated using 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][NTf₂]) as the ionic liquid (IL) extractant. The IL effectively extracted Li⁺ from the aqueous phase in bulk extraction, demonstrating its potential for lithium recovery. However, the low interfacial tension between the IL and aqueous phases posed challenges for phase separation. The application of SAM and Zdol coatings effectively mitigated this issue. Overall, integrating tailored surface chemistry with the slope-plate MPSE design shows great promise as an efficient and scalable platform for studying liquid–liquid separation and optimizing ionic liquid–based extraction processes for lithium recovery from saline sources.

3D printing↗

DOE OSTI2025

Nanoporous Fe 2 O 3 and Soluble Fe(II) Intermediates Accelerate the Electrodeposition of Fe in NaOH(aq)

Electrochemical conversion of iron oxide to iron metal can enable low-cost batteries for long duration energy storage and zero-emissions ironmaking for steel. Iron oxides, such as hematite, can be electrochemically reduced to metallic iron in concentrated alkaline electrolytes at modest temperatures, but the relative influences of solid-state and dissolved intermediates at practical reaction rates remains unclear. Here, in this study, we prepare a homologous set of well-defined hematite particles to measure how the nanoscale morphology of oxides controls both their reactivity and apparent reduction mechanism in concentrated hydroxide. Correlated electron microscopy and rotating-ring-disk-electrode measurements revealed that nanoporous hematite and solid intermediates formed iron via a dissolution-redeposition pathway. In contrast, dense hematite particles directly formed iron metal via reactive fracture. While previous studies on iron electrowinning have primarily emphasized the role of particle diameter at the micron scale, these results demonstrate the importance of the dissolution-redeposition pathway to support rapid reaction rates and suggest that nanoscale porosity controls iron oxide reactivity at temperatures <100 °C. Therefore, iron-oxide-to-metal electrolyzers and fast-charging iron-air batteries supported by curtailed electricity can increase the rate of metal formation by accelerating fracture and dissolution in reactant oxides.

TEM↗

DOE OSTI2025

Blue Carbon Stocks Along the Pacific Coast of North America Are Mainly Driven by Local Rather Than Regional Factors

Coastal wetlands, including seagrass meadows, emergent marshes, mangroves, and temperate tidal swamps, can efficiently sequester and store large quantities of sediment organic carbon (SOC). However, SOC stocks may vary by ecosystem type and along environmental or climate gradients at different scales. Quantifying such variability is needed to improve blue carbon accounting, conservation effectiveness, and restoration planning. We analyzed SOC stocks in 1,284 sediment cores along >6,500 km of the Pacific coast of North America that included large environmental gradients and multiple ecosystem types. Tidal wetlands with woody vegetation (mangroves and swamps) had the highest mean stocks to 1 m depth (357 and 355 Mg ha −1 , respectively), 45% higher than marshes (245 Mg ha −1 ), and more than 500% higher than seagrass (68 Mg ha −1 ). Unvegetated tideflats, though not often considered a blue carbon ecosystem, had noteworthy stocks (148 Mg ha −1 ). Stocks increased with tidal elevation and with fine (<63 μm) sediment content in several ecosystems. Stocks also varied by dominant plant species within individual ecosystem types. At larger scales, marsh stocks were lowest in the Sonoran Desert region of Mexico, and swamp stocks differed among climate zones; otherwise stocks showed little correlation with ecoregion or latitude. More variability in SOC occurred among ecosystem types, and at smaller spatial scales (such as individual estuaries), than across regional climate gradients. These patterns can inform coastal conservation and restoration priorities across scales where preserving stored carbon and enhancing sequestration helps avert greenhouse gas emissions and maintains other vital ecosystem services.

emergent marsh↗

DOE OSTI2026

Shifts in rain-snow partitioning drive faster water transit times in the US Pacific Northwest

Water transit times strongly influence water quality, temperature, and seasonal hydrologic response of river systems. How water transit times may shift under future climates remains unconstrained, especially in mountainous regions experiencing rapid snowpack declines. Here, we estimated historical (2006–2013) and future (2086–2093) water transit times in five headwater catchments within the U.S. Pacific Northwest using sequential precipitation input tagging within the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model. Our results indicate water transit times are 18% (35–64 days) faster on average under the Representative Carbon Pathways (RCP) 8.5 climate scenario due to shifts in rain-snow partitioning, with higher fractions of younger water in the wet season and older water in the dry season. These results suggest shifts in rain-snow partitioning in snowmelt dominated catchments of the Pacific Northwest will shorten water transit times leading to likely impacts on regional water quality, temperature, and hydrologic seasonality.

Butler, Zachariah [Oregon State Univ., Corvallis, ↗

DOE OSTI2026

CADIS and FW-CADIS Variance Reduction in Gamma Transport for Predicting Prompt Forensics Signatures

The goal of prompt nuclear forensics is to determine the characteristics of a nuclear detonation based on the signatures available almost immediately after the explosion. An important characteristic is the reaction time history (RTH), a measure of the device’s rate of neutron multiplication. The RTH can be estimated by observation of the gamma radiation emitted from the detonation, which can be detected directly or observed indirectly as Teller light. Gamma transport simulations used to predict these radiation fields are often modeled stochastically using the Monte Carlo N-Particle (MCNP) code, which can be a computationally demanding task due to the number of particle histories needed to achieve statistical convergence. In an attempt to improve the efficiency of these calculations, we evaluate two variance reduction techniques: Consistent Adjoint-Driven Importance Sampling (CADIS) and Forward-Weighted Consistent Adjoint-Driven Importance Sampling (FW-CADIS). These methods use a deterministically calculated adjoint flux to create weight windows and source biasing that guide MCNP sampling. We study the utility of CADIS and FW-CADIS for their use in MCNP gamma transport for nuclear forensics prediction simulations. Furthermore, the results demonstrate that both CADIS and FW-CADIS improve the accuracy for forensics-focused simulations, with CADIS being most beneficial in direct detection and FW-CADIS being ideal for computing a global Teller light source.

CADIS↗

DOE OSTI2025

STEM Ptychographic Holography of Electric and Magnetic Potentials

The development of fast an efficient direct electron imaging detectors have enabled the advancement of phase-imaging techniques in STEM such as iterative ptychography. As beneficial as these techniques are to imaging phase objects, the information recorded in the raw data is due to phase gradients across the probe, so it can be challenging to reconstruct slowly varying phase at lower spatial frequencies such as those induced by electric or magnetic potentials within the specimen. STEM holography [1,2] is an interferometric 4D-STEM technique where electrons in the beam are coherently divided into a superposition of two or more spatially separated probes which are then scanned over the specimen. For example, in a two-beam superposition, the two probes form overlapping bright field discs at the detector which then interfere (left of Fig. 1). Furthermore, if one probe passes through vacuum while the other transmits through the specimen, the resulting relative phase shift can be measured by recording shifts in the interference pattern. STEM holography is thus directly sensitive to the phase of the probe relative to the reference beam, and this phase can be measured regardless of the convergence angle of the probe, unlike single beam ptychography.

Biological Sciences↗

DOE OSTI2025

Experimental determination of energy-level structures of diamond silicon-vacancy centers in off-axis magnetic fields

Here, we report the development of an experimental approach to efficiently determine the energy level structure of an individual silicon vacancy (SiV) center in a magnetic field along an arbitrary direction. This approach uses two coupling rates (one each for the ground and the excited states) to characterize the combined effects of static strain and dynamic Jahn-Teller coupling and exploits the fact that orbital Zeeman effects vanish when the magnetic field is normal to the SiV axis. With an analytical expression for the energy level structure of the SiV under a transverse magnetic field, the two coupling rates can be directly derived from two measurements: one on the frequency separation between two spin-conserved transitions and the other on the coherent population trapping resonance of the SiV ground spin states. A detailed comparison between the numerical calculation and the experimental result on the dependence of the spin-conserved splitting on both the amplitude and direction of the magnetic field further reveals unequal orbital magnetic coupling for the ground and excited states, indicating that unequal orbital quenching factors are needed for an accurate description of the SiV energy level structure in a magnetic field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2025

First Direct-Detection Results on Sub-GeV Dark Matter Using the SENSEI Detector at SNOLAB

Here, we present the first results from a dark matter search using six Skipper-CCDs in the SENSEI detector operating at SNOLAB. We employ a bias-mitigation technique of hiding approximately 46% of our total data and aggressively mask images to remove backgrounds. Given a total exposure after masking of 100.72 gram-days from well-performing sensors, we observe 55 two-electron events, 4 three-electron events, and no events containing 4–10 electrons. The two-electron events are consistent with pileup from one-electron events. Among the 4 three-electron events, 2 appear in pixels that are likely impacted by detector defects, although not strongly enough to trigger our “hot-pixel” mask. We use these data to set world-leading constraints on sub-GeV dark matter interacting with electrons and nuclei.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Additive Manufacturing of Lattice Structures for Catalyst Applications

Abstract The design and fabrication of Inconel 718 open-pore lattice structures via Laser Powder Bed Fusion (LPBF) has been investigated in this research, focusing on applications such as catalyst supports in jet fuel production. The study explores the impact of laser power and scanning speed on the geometrical resolution of these structures aiming to achieve high porosity (porosity > 60%) and specific pore sizes ranging from 500–1000 μm, intending to serve as catalyst supports, replacing conventionally manufactured foams to reduce costs. Results demonstrate the significant influence of processing parameters on the geometrical aspects of printed lattice structures, with laser power having a more pronounced effect on geometrical accuracy than scanning speed. Additionally, the mechanical properties of the printed lattice structures showed a correlation with the lattice strut sizes, as lattices with less porosity and thicker struts resulted in higher maximum shear stress.

36 MATERIALS SCIENCE↗

DOE OSTI2025

A Unified Interpretation of Variability in Precipitation Isotope Ratios

Abstract Several mechanisms have been proposed to explain why the isotope ratios of precipitation vary in space and time and why they correlate with other climate variables like temperature and precipitation. Here, we argue that this behavior is best understood through the lens of radiative transfer, which treats the depletion of atmospheric vapor transport by precipitation as analogous to the attenuation of light by absorption or scattering. Building on earlier work by Siler et al., we introduce a simple model that uses the equations of radiative transfer to approximate the two-dimensional pattern of the oxygen isotope composition of precipitation ( δ p ) from monthly mean hydrologic variables. The model accurately simulates the spatial and seasonal variability in δ p within a state-of-the-art climate model and permits a simple decomposition of δ p variability into contributions from gradients in evaporation and the length scale of vapor transport. Outside the tropics, δ p is mostly controlled by gradients in evaporation, whose dependence on temperature explains the positive correlation between δ p and temperature (i.e., the temperature effect). At low latitudes, δ p is mostly controlled by gradients in the transport length scale, whose inverse relationship with precipitation explains the negative correlation between δ p and precipitation (i.e., the amount effect). This suggests that the temperature and amount effects are both mostly explained by the variability in upstream rainout, but they reflect distinct mechanisms governing rainout at different latitudes. Significance Statement The isotopic composition of precipitation has long been used to make inferences about past climates based on its observed relationship with precipitation in the tropics and with temperature at higher latitudes. These relationships—known as the “amount effect” and “temperature effect,” respectively—have been attributed to many different mechanisms, most of which are thought to operate at either high or low latitudes but not both. Here, we present a unified framework for interpreting the isotope variability that can explain the latitude dependence of the temperature and amount effects despite making no distinction between high and low latitudes. Although our results are generally consistent with certain interpretations of the amount effect, they suggest that the temperature effect is widely misunderstood.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Data and script associated with “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest”

This data package contains the data and code to use and run the Water Tracer enabled version of the Weather Research and Forecasting Hydrologic model (WT-WRF-Hydro) with the Sequential Precipitation Input Tagging (SPIT) framework. It is associated with the publication “Shifts in Rain-Snow Partitioning Drive Faster Water Transit Times in the US Pacific Northwest” published in Scientific Reports (Butler et al., 2026; https://doi.org/10.1038/s41598-026-46539-1). We use the Continental U.S. (CONUSII; Rasmussen et al., 2021) dataset to force the model with an historical climate (2006–2013) and a future climate (2086–2093) with a representative carbon pathway (RCP) 8.5 scenario. We use the model to calculate water transit times in five headwater catchments within the U.S. Pacific Northwest. We also show key hydrologic and environmental variables that affect water transit times and changes in the future. Finally, we use observed data to validate the model such as stream water isotopes, snowpack characteristics, and stream discharge. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to a readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. The data package consists of 11 folders: (1) "Figures" contains the exported figures used in the manuscript; (2) "Model_Isotope_Date" contains the WT-WRF-Hydro isotope date used in model validation; (3) “Model_Outputs_Future” contains the WT-WRF-Hydro future climate outputs; (4) “Model_Outputs_Historical” contains the WT-WRF-Hydro historical climate outputs; (5) “Model_Outputs_Weights_Areas” contains the WT-WRF-Hydro weights per catchment used to calculate water transit times and isotopes in stream water; (6) “MODIS_data_scripts” contains data used to validate snow conditions in the study area; (7) “Observed_Flow_Data” contains the observed streamflow data used in model validation; (8) “Observed_Isotope_Data” contains the observed stream water isotope data used in model validation; (9) “Scripts” contains the Python scripts used to general results and the figures; (10) “Statistic_Outputs” contains the water transit time statistical outputs reported in this manuscript; (11) “Validation_SNOTEL” contains the SNOTEL data used in model validation. The files in this data package have the following file extensions: .tif, .txt, .csv, .pdf, .py, .jpg, and .png.

American River↗

DOE OSTI2025

Additive Manufacturing of Lattice Structures for Catalyst Applications

Ghanadi, Nahal [Oregon State University] (ORCID:00↗

DOE OSTI2025

Applied Research and Development to Support Open Water Testing at PacWave – Task 5: Development of additively manufactured, functionally graded, corrosion resistant clads for wave energy applications

In this task, we focused on developing corrosion-resistant claddings for wave energy applications. Wave energy systems are exposed to saline conditions, which are corrosive to many metallic structural materials (e.g., carbon steel). Corrosion-resistant (stainless) steels are typically alloyed with >18% chromium (Cr) and >8% nickel (Ni), which dramatically raises material costs and can hinder the development of wave energy systems; thus, coatings are a necessary corrosion protection method for most. Non-metallic coatings (paint, epoxy) have shorter service lives, limited resistance to mechanical stress and wear, plus additional costs of inspection and eventual replacement. Therefore, overlay stainless steel (SS) claddings have a cost-effective use case for protecting components from corrosion, particularly for those that may be subject to mechanical stress / wear and with long service lives.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

Phenotypically anchored transcriptomics across diverse agrichemicals reveals conserved pathways and unique gene expression signatures in zebrafish

Agrichemicals such as herbicides, fungicides, insecticides, and biocides are widely used in agriculture, yet some are associated with adverse effects in humans and the environment. While many of these chemicals have been extensively studied in vitro and are included in the EPA’s ToxCast program, comprehensive in vivo comparisons using RNA sequencing across structurally diverse agrichemicals, in a single screening platform, are lacking. In this study, we examined structurally diverse agrichemicals found in the U.S. Environmental Protection Agency’s (EPA) Toxcast Phase I and II library by statically exposing early life stage zebrafish at 6 h post fertilization (hpf) until 120 hpf at concentrations ranging from 0.25 to 100 µM. Morphological outcomes were assessed at 120 hpf across 10 endpoints, including yolk sac edema, craniofacial malformations, and axis abnormalities. Chemicals that produced robust concentration-response relationships were selected for transcriptomic profiling. For transcriptomic analysis, zebrafish were statically exposed to each chemical and sampled at 48 hpf, prior to the onset of morphological effects observed at 120 hpf. Differential expression analysis identified between 0 and 4,538 differentially expressed genes (DEGs) per chemical, with no clear correlation to morphological severity. Both DEG and co-expression network analyses revealed chemical-specific expression patterns that converged on shared biological pathways, including neurodevelopment and cytoskeletal organization. Key regulatory genes such as mylpfa and krt4 were identified within co-expression modules, suggesting their potential role in conserved toxicity mechanisms. Semantic similarity analysis of enriched gene ontology (GO) terms, when compared to existing datasets, highlighted gaps in the annotation of neurodevelopmental processes, indicating that some in vivo effects may not be fully captured by current curated resources. The results provide new insights into the modes of action of diverse agrichemicals and establish a framework for understanding how agrichemical structure relates to biological function in a vertebrate model.

agrichemical↗

DOE OSTI2025

Real-Time Wave Energy Converter Control Using Instantaneous Frequency

Wave Energy Converters (WECs) rely on effective Power Take-Off (PTO) control strategies to maximize energy absorption under dynamic sea conditions. Traditional hydrodynamic modeling techniques may require computationally intensive convolution calculations, making real-time control implementation challenging. This paper presents an alternative approach by leveraging instantaneous frequency estimation to dynamically adjust PTO damping in response to varying wave frequencies. Two real-time frequency estimation methods are explored: the Hilbert Transform (HT) and Phase-Locked Loop (PLL). The Hilbert Transform method provides accurate frequency tracking but introduces a delayed response due to its dependence on causal data. Conversely, the PLL approach demonstrates strong potential in frequency tracking but requires careful gain tuning, particularly in complex sea states. Comparative evaluations across multiple test cases—including sinusoidal variations, amplitude steps, frequency step changes, and real-world JONSWAP spectrum waves—highlight the strengths and limitations of each method. The two different PTO control techniques across the various frequency estimation methods were tested under real-sea states using a state-space model of a point-absorbing Wave Energy Converter. The Capture Width Ratio (CWR) is used as a performance metric, with results showing that the HT achieves a 10.6% improvement, while the PLL estimation yields a 0.9% improvement relative to the fixed parameter control baseline. These results highlight the effectiveness of real-time frequency estimation in improving energy absorption compared to static control parameters.

WEC control↗